Contact (or call) centers where groups of service representatives interact with users or customers, for example by telephone but also by other communications methods, are known in the art. Generally, agents (e.g., human employees, but sometimes automated “bots”) in a contact center interact with, or talk to, customers or clients in order to sell products or services and/or solve issues or problems related to products or services. For example, a customer who has a problem or issue with a product or service calls (e.g., via telephone or other voice communications channels) a call center and discusses the issue with an agent. An interaction may be for example a conversational exchange between one or more people, e.g. a verbal conversation, a conversation via e-mail, or a conversation via text or other messages. Such interactions may be recorded, e.g., by audio recording, recordings of texts, etc. Recorded interactions may be transcribed such that a textual representation of interactions is produced. For example, a transcription of a recording of a conversation between an agent and a customer may enable searching for words or phrases mentioned in the conversation.
Identifying and/or characterizing, in a contact center, problems and/or issues that customers have with products and services is a challenge not yet fully met by the industry. For example, known system and methods do not offer an automated way of determining which products or services customers complain about. Moreover, known system and methods do not offer an automated way of determining, identifying or pinpointing the specific problem or issue related to a product or service.
Currently, human analysts in a contact center perform analysis of interactions, e.g., by listening to recorded interactions, examining transcriptions of interactions and so on. In other cases, analysis is performed, by a system, based on transcriptions of calls. However, known systems and methods suffer from a number of drawbacks. For example, known systems and methods rely on speech to text (STT) transformations of calls (known in the art as transcriptions) which typically include errors. In addition, known systems and methods are time consuming and require highly skilled (and costly) human professionals.